DMD was initially proposed as a dimensionality reduction technique
that extracts dominant spatio-temporal coherent structures from high-dimensional time-series data [1]}.
In particular, DMD identifies the leading-order spatial eigenmodes of the matrix \(A\)  in (REF ), along with a linear model for how the amplitudes of these coherent structures evolve in time.
DMD has been applied to a range of systems, as summarized in the monograph [2]} and
the recent review by Schmid [3]}.
